Python STEM Essentials

Python STEM Essentials, available at $59.99, has an average rating of 4.62, with 8 lectures, based on 80 reviews, and has 626 subscribers.

You will learn about python libraries for scientific analysis numerical integration, interpolation of data, curve fitting, differential equations how to calibrate a photon detector used for medical imaging how to solve biological equations governing populations of various species This course is ideal for individuals who are Undergraduate students just getting into research or Graduate students that want to use python as their primary language for research or Engineers looking to use python to analyze data It is particularly useful for Undergraduate students just getting into research or Graduate students that want to use python as their primary language for research or Engineers looking to use python to analyze data.

Enroll now: Python STEM Essentials

Summary

Title: Python STEM Essentials

Price: $59.99

Average Rating: 4.62

Number of Lectures: 8

Number of Published Lectures: 8

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 13

Original Price: $69.99

Quality Status: approved

Status: Live

What You Will Learn

python libraries for scientific analysis
numerical integration, interpolation of data, curve fitting, differential equations
how to calibrate a photon detector used for medical imaging
how to solve biological equations governing populations of various species

Who Should Attend

Undergraduate students just getting into research
Graduate students that want to use python as their primary language for research
Engineers looking to use python to analyze data

Target Audiences

Undergraduate students just getting into research
Graduate students that want to use python as their primary language for research
Engineers looking to use python to analyze data

This course is an introduction to useful python functionality in scientific research and engineering applications that is rarely taught rigorously in universities. It begins with an overview of required numerical libraries, such as NumPy and SciPy, and eventually moves on to techniques such as interpolation, curve fitting, and solving systems of differential equations. A heavy emphasis is placed on real world examples; datasets will be examined in lectures, and students will expand on the analysis of these datasets in the 5 thorough course assignments.

At the end of this course, you will feel comfortable using python as your preferred programming language in a research setting. In addition (and most importantly) you will have learned to properly interpret output, such as the error on parameters in curve fitting, and what an interpolated data point actually means.

Some datasets examined include: radioactive particle energy measurements obtained in a crystal detector, photon spectrum in a radiotherapy unit used to treat cancer patients, and photon attenuation data in a block of lead. In the differential equation section, we will look at solving the following systems of equations: the pendulum, projectile motion with friction, the Lotka Volterra equations, and finally (a question that combines most concepts of the course) dark matter evolution throughout the history of the universe.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Essentials

Lecture 1: Essentials

Chapter 3: Integration

Lecture 1: Integration

Chapter 4: Interpolation

Lecture 1: Interpolation

Chapter 5: Curve Fitting

Lecture 1: Curve Fitting: Theory

Lecture 2: Curve Fitting: Real World Examples

Chapter 6: Differential Equations

Lecture 1: Differential Equations: Theory

Lecture 2: Differential Equations: Real World Examples

Instructors

Luke Polson
PhD Candidate

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 1 votes
4 stars: 20 votes
5 stars: 58 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu